BLUP Method Research Articles

Rendimento de grãos em feijão preto: o componente que mais interfere no valor fenotípico é o ambiente

O objetivo deste trabalho foi avaliar os componentes da variância fenotípica para o caráter rendimento de grãos a fim de gerar informações que auxiliem o melhoramento de plantas e verificar a sensibilidade genotípica entre genótipos de feijão do grupo preto. Para tanto, foi avaliado o caráter rendimento de grãos de 12 genótipos de feijão em 10 ambientes do Estado de Santa Catarina, por meio do método REML/BLUP. A decomposição dos componentes da variância fenotípica permitiu ampliar as inferências sobre os resultados obtidos para o caráter rendimento de grãos além daquelas tradicionalmente utilizadas na avaliação de linhagens. O genótipo BRS Campeiro foi o que apresentou maior média de rendimento de grãos e ainda o que obteve o maior valor predito, podendo ser indicado para todos ambientes avaliados. Nos ambientes 1 (2004/Canoinhas), 2 (2005/Canoinhas), 9 (2004/Ponte Serrada) e 10 (2005/Ponte Serrada), o valor de rendimento de grãos, em todos os genótipos avaliados, foi acima da média geral. Os genótipos CHP 9858, CHP 9859, CHP 9954 e CHP 9965 revelaram uma adaptabilidade específica ao ambiente 6 (2005/Ituporanga).

Factors Affecting Accuracy From Genomic Selection in Populations Derived From Multiple Inbred Lines: A Barley Case Study

We compared the accuracies of four genomic-selection prediction methods as affected by marker density, level of linkage disequilibrium (LD), quantitative trait locus (QTL) number, sample size, and level of replication in populations generated from multiple inbred lines. Marker data on 42 two-row spring barley inbred lines were used to simulate high and low LD populations from multiple inbred line crosses: the first included many small full-sib families and the second was derived from five generations of random mating. True breeding values (TBV) were simulated on the basis of 20 or 80 additive QTL. Methods used to derive genomic estimated breeding values (GEBV) were random regression best linear unbiased prediction (RR-BLUP), Bayes-B, a Bayesian shrinkage regression method, and BLUP from a mixed model analysis using a relationship matrix calculated from marker data. Using the best methods, accuracies of GEBV were comparable to accuracies from phenotype for predicting TBV without requiring the time and expense of field evaluation. We identified a trade-off between a method's ability to capture marker-QTL LD vs. marker-based relatedness of individuals. The Bayesian shrinkage regression method primarily captured LD, the BLUP methods captured relationships, while Bayes-B captured both. Under most of the study scenarios, mixed-model analysis using a marker-derived relationship matrix (BLUP) was more accurate than methods that directly estimated marker effects, suggesting that relationship information was more valuable than LD information. When markers were in strong LD with large-effect QTL, or when predictions were made on individuals several generations removed from the training data set, however, the ranking of method performance was reversed and BLUP had the lowest accuracy.

Heritability and genetic trends of number of kits born alive in a synthetic maternal rabbit line

Heritability and genetic trends for number of kits born alive in a synthetic maternal rabbit line were estimated in this study. The data were collected from 1999 to 2007 on 5640 kindlings of 1425 does. The total number of animals in the pedigree was 2576. The mean number of kits born alive was 8.42 with a standard deviation of 2.87. Genetic parameters and breeding values were estimated using the VCE-5 and PEST software based on the REML and BLUP methods using a repeatability animal model. For litter size, the first, second and third parities were treated as repeated trait, while the fourth and further parities were pooled and considered as same repetition. The estimated heritability and the repeatability for number of kits born alive were low (0.05 and 0.14). The observed selection response was about 0.04 rabbits/year.

Growth performance of station tested rams in Slovenia

In Slovenian sheep breeding programme rams from top flocks are selected for performance test on growth in two test stations with different conditions. The aim of this work was to develop a model that could be used for genetic evaluation using BLUP method. Data on 3,500 rams of several breeds were collected from breeding programme database and analysed with linear mixed model. The selected model accounted for the following fixed effects: breed, station, age at weighing as quadratic polynomial nested within breed and station, parity and the number of liveborn littermates. Additionally, several random effects were included: origin, origin-year interaction, season as day of weighing, and the effect of individual ram. Results showed differences in growth between breeds and stations, higher body weight for rams born as single lambs and lower body weight for rams born in first parity. Variance component ratios are reported for random effects. The analysis did not include pedigree information, but it was shown a considerable variance between rams.

Quantitative analysis of genetic improvement of milk production phenotypes in Simmental cows

Results of the effect of direct and indirect selection on quantitative properties of milk production of first calving Simmental cows in Serbia, are presented in the paper. Analysis of quantitative phenotypic parameters was carried out in four breeding regions and certain number of smaller farms where 1319 daughters of 13 bull sires were reared. Results of the analysis were obtained by application of mathematical-statistical data analysis, using mixed models (Harvey, 1990). Mathematical-statistical analysis of data was carried out using linear methods with fixed effect, through method of least squares (LS method), and for evaluation of bull breeding value mixed model of random bull sire effect was used (BLUP method). Based on obtained results it was established that analyzed breeding region has statistically highly significantly (**P<0.01.) caused deviations of production phenotypes from general average. Season and year of calving (*P<0.05.) have caused significant variations of production properties. .

Using LASSO to estimate marker effects for Genomic Selection

Here we suggest a least absolute shrinkage and selection operator (LASSO) approach to estimate the marker effects for genomic selection using the least angle regression (LARS) algorithm, modified to include a cross–validation step to define the best subset of markers to involve in the model. The LASSO-LARS was tested on simulated data which consisted of 5,865 individuals and 6,000 SNPs. The last generations of this dataset were the selection candidates. Using only animals from generations prior to the candidates, three approaches to splitting the population into training and validation sets for cross-validation were evaluated. Furthermore, different sizes of the validation sample were tested. Moreover, BLUP and Bayesian methods were carried out for comparison. The most reliable cross-validation method was the random splitting of overall population with a validation sample size of 50% of the reference population. The accuracy of the GEBVs (correlation with true breeding values) in the candidate population obtained by LASSO-LARS was 0.89 with 156 explanatory SNPs. This value was higher then those obtained by using BLUP and Bayesian methods, which were 0.75 and 0.84 respectively. It was concluded that LASSO-LARS approach is a good alternative way to estimate markers effects for genomic selection.

Association of the <i>BoLA-DRB3</i> alleles with estimated breeding value for somatic cell count in Polish dairy cattle

Abstract. Introducing resistance to mastitis into breeding programmes for dairy cattle seems to be one of the possible methods for limiting the increasing number of mastitis cases. Looking for candidate genes for genetic markers is one of the strategies. The BoLA–DRB3 alleles have considerable promise as potential mastitis marker. The objective of the study was to evaluate relationships between two BoLA–DRB3 alleles (BoLA–DRB3.2*16 and BoLA-DRB3.2*23) and estimated breeding value (EBV) for somatic cell count (SCC) in Polish dairy cattle. A total of 525 Polish Holstein cows in two experimental farms were evaluated for test-day SCC. The polymorphism of BoLA–DRB3 gene was identified using the MPT-PCR method. The variance components for test-day SCC were estimated by the REML method using animal model. The breeding value of SCC was calculated according to the BLUP method. Linear contrast between model-adjusted breeding values of SCC for all animals was used to test for differences between genotypes. In Polish Holstein cows population BoLA allele DRB3.2*23 was associated with increase of EBV for SCC in milk. It was observed increase of EBV for SCC from cows carrying this allele comparing to cows carrying BoLA–DRB3.2*16 (p ≤0.07) or other alleles (p ≤0.01).

Potential of maize single-cross hybrids for extraction of inbred lines using the mean components and mixed models with microsatellite marker information

The present study examined the importance of mean (m+a' and d) components in the performance of single-cross hybrids for the formation of new populations and determined the contribution of the mixed model (best linear unbiased predictor of random effects, BLUP) method associated with molecular markers for the choice of crosses to obtain interpopulation hybrids. Ten single-cross commercial hybrids of different companies were used for this purpose, producing all possible double-cross hybrids through a complete diallel. The hybrids were evaluated in 15 locations in the agricultural year 2005/2006, using randomized complete block design with three repetitions. In three of these locations, estimates of m+a' and d were obtained. DNA was extracted from the single-cross hybrids and 20 SSR primers were used, nine of which were linked to QTL for yield. There was no correlation between m+a' of the single-cross hybrids with general combining ability (r = -0.15) inferring that populations with lines with high means do not always produce good hybrids. Also, it was observed that the correlation between the genetic distances with specific combining ability varied from 0.31 to 0.80 in the inter-group hybrids, while in the intra-group hybrids these estimates were low and non-significant. The heritability value obtained by BLUP was high and greater than that obtained by ordinary least squares (h(2) = 0.95 and 0.86), confirming the greater selection accuracy by the BLUP method. There were no differences between the accuracy values obtained with microsatellite information and without this information, inferring that there was no advantage of progenitor information on balanced data. It can be concluded that the estimate m+a' should not be used as a deciding parameter about the potential for extracting lines from a given population. The heritability and accuracy values obtained by BLUP allow the inference that it is possible to predict success in the choice of progenitors to obtain interpopulation hybrids.

Genotypic evaluation of accessions and individual selection in Stylosanthes spp. by simulated BLUP method

Genetic improvement programs ofperennialforage legumes in Brasil evaluate accessions in row plots without considering the genetic variability within accessions. Individual plant evaluations would not only allow for selection ofthe best accessions but also for the best individuais within accessions. This procedure is however more labor-intensive and expensive. The effectiveness ofusing the simulated individual BLUP selection method (BLUPIS) was assessed in a trial with Stylosanthes capitata and S. guianensis in a completely randomized block design with 35 accessions, six plants per plot and six andfive replications, respectively. The method can be applied when only total plot yields are measured and provide selection at the individual plant levei. Results showed a high correlation between selection by the traditional BLUP and the alterna tive BLUPlS methods. The latter is recommendedfor improving species in which individual plant evaluations are difficult.

Results of the application of the technology of genetic improvement of Simmental cattle population in Serbia

Results of production traits obtained from first calving cows and evaluation of the breeding value of bull sires of Simmental breed in Serbia. Data was analyzed using the method of least squares and for evaluation of bulls' breeding value mixed model of random sire effect (BLUP method). Based on obtained results it was established in statistical analysis that breeding region had highly significantly affected (P<0.01) the deviation of production traits from the general average. Considerable deviation from the general average was caused by the year and season of calving (P<0.05), and interaction of breeding region and calving season contributed to high variation in yield of milk and milk fat (P<0.01).

Estimation of genetic parameters based on individual and group mean records in laying hens

1. The study was conducted to estimate the heritability, genetic correlations and breeding values of laying hens based on individual records and group mean records. 2. Records of two pure lines from a commercial breeding programme of White Leghorns from three generations housed in single cages and in group cages were used. A total of 8483 and 8817 individual records of lines A and D, respectively, and a total of 1358 (line A) and 1161 (line D) group mean records were analysed. 3. An animal model using Restricted Maximum Likelihood (REML) was used to estimate variance components of individual records. Group mean records were analysed using the sire model, taking heterogeneity of error variance and correlated residual effects into account. Breeding values of sires were estimated based on the BLUP method using a multivariate sire model. Spearman Rank correlations were used to compare sire breeding values estimated from individual records and from group mean records. The traits studied were monthly egg production, cumulative production and egg weight. 4. Heritability estimates based on individual records were higher than from group mean records. Heritabilities for cumulative production records were higher than for monthly production, based on individual as well as group mean records. The estimates of genetic correlations between monthly egg production and cumulative production were moderate to high. Egg production and egg weight recorded individually were highly genetically correlated with those recorded on group means. Sire breeding values estimated from individual records showed high correlations with those from group mean records. 5. Differences in the ranking of sire breeding values estimated from individual vs group mean records were negligible, indicating that no genotype × environment interaction exists. Selection based on individual performance records of laying hens housed in single cages could give a good response on performance of laying hens housed in group cages. Cumulative egg production over periods 1 to 6 is the best trait for the selection programme.

Selection against genetic defects in conservation schemes while controlling inbreeding

We studied different genetic models and evaluation systems to select against a genetic disease with additive, recessive or polygenic inheritance in genetic conservation schemes. When using optimum contribution selection with a restriction on the rate of inbreeding (ΔF) to select against a disease allele, selection directly on DNA-genotypes is, as expected, the most efficient strategy. Selection for BLUP or segregation analysis breeding value estimates both need 1–2 generations more to halve the frequency of the disease allele, while these methods do not require knowledge of the disease mutation at the DNA level. BLUP and segregation analysis methods were equally efficient when selecting against a disease with single gene or complex polygene inheritance, i.e. knowledge about the mode of inheritance of the disease was not needed for efficient selection against the disease. Smaller schemes or schemes with a more stringent restriction on ΔF needed more generations to halve the frequency of the disease alleles or the fraction of diseased animals. Optimum contribution selection maintained ΔF at its predefined level, even when selection of females was at random. It is argued that in the investigated small conservation schemes with selection against a genetic defect, control of ΔF is very important.

Linkage disequilibrium in two‐stage marker‐assisted selection

Linkage disequilibrium in two‐stage marker‐assisted selection

A Comparison of Breeding Value Predictors for Longevity Using a Linear Model and Survival Analysis

A comparison was made among breeding values of sires for longevity that were obtained by different methods: phenotypic averages of daughters using only uncensored records, BLUP using only uncensored records, survival analysis using only uncensored records, and survival analysis using both censored and uncensored records. Two data files were used: one contained data from small herds, and the other contained data from large herds. The results from both data files were similar. Different methods of predicting breeding values resulted in different rankings of sires. The results obtained using phenotypic averages were weakly correlated (≤0.46) with those results obtained using the other methods of prediction. The REML BLUP had strong correlations (≤−0.91) with the survival analysis predictor if the same data were used, and correlations weakened (≤−0.60) when censored records were included in the survival analysis. The correlations are negative because the linear method analyzed longevity, and survival analysis measured the risk of being culled, which has an antagonistic relationship with longevity. The results from REML BLUP and survival analysis methods differed mainly because of the different data that were used (uncensored only versus both censored and uncensored).

Genetic Evaluation of Sires and Environmental Factors Influencing Best Racing Times of Thoroughbred Horses in Japan.

The sire effect and the fixed effects of sex, training center, type of course, specific racetrack, horse age and track condition were evaluated regarding best racing times of thoroughbred horses. The records of best racing times at the Japan Racing Association were collected from the electronic racing book. The data set was edited so that each sire was required to have at least twenty progeny in the racing distances of 1200m and 1800m. The total numbers o f sires and progeny were 34 and 1486 for 1200m and 34 and 1520 for 1800m. First, the least-squares analysis of variance was carried out by using the linear model which included the sire effect and the six fixed effects. Second, heritabilities for best racing times were calculated, and additionally sire evaluations were carried out by using the sire model of the BLUP method. As a result of analysis of variance, almost all effects included in the linear model were significant for both racing distances. The sire, type of course, horse age and interaction between the type of course and track condition had a highly significant effect on best racing times. Estimates of heritability were 0.11 and 0.09 for 1200 m and 1800 m, respectively. Rankings of sires' breeding values based on progeny records were quite different for the two racing distances. The Spearman rank correlation coefficient for these rankings was 0.350 (P<0.05).

A Computationally Simple Bayesian Method for Estimation of Heterogeneous Within-Herd Phenotypic Variances

Heterogeneous variance among subclasses of the data (e.g., herds) is a potential source of bias in livestock genetic evaluation. The BLUP method can account for such heterogeneity if variance components within each subclass are known; unfortunately, information within a particular subclass is generally insufficient to estimate variances or variance components accurately. Procedures based on empirical Bayes methods and structural models for variance components have been derived but are not yet computationally feasible on a large scale. Therefore, computationally simpler approximations based on phenotypic variances have been proposed and utilized, but these lack, so far, theoretical support. In this study, a Bayesian procedure for combining within- and across-subclass phenotypic variances is presented, and a numerical example is given. This method offers the computational simplicity of other approximate procedures based on phenotypic variances, but it also possesses a stronger theoretical justification. In a simulation study involving an average of approximately 1.6million observations in 44,000 region-herd-year-parity subclasses, the Bayesian method compared favorably with other currently available methods for combining within- and across-subclass phenotypic variances.

Effect of errors in genetic and environmental variances on the BLUP estimates of sire breeding values

Summary — The BLUP method for the estimation of breeding values requires the knowledge of the ratio of the residual over the genetic variance or of the heritability value (hThe bias in the breeding value estimates caused by a wrong choice of h has been examined by: (a) analysis of 11 populations simulated by varying the h value of the trait and the offspring size of each sire (n); (b) analysis of the weaning weights of 2055 Angus beef calves (725 dams bred to 89 sires). The breeding value estimates were found to be different depending on the h value chosen. This error causes rank changes between sires and, consequently, a possible wrong choice of the subjects to be selected. For a 40% error in h and 5 < n < 60, we found that the % bias : 26.2 + 47.9/n- 27.9irWhen the data structure makes a serious bias likely to occur in the breeding value estimates, it is recommended to use a method for the variance components estimation, even if this is more time consuming from a computing point of view.

Selection theory with overlapping generations

The implications for selection of genetic differences between animals of different ages and between progeny of the same age but from parents of different ages are discussed. Correct definitions of generation length and of selection differential when replacements are selected disproportionately from parental-age subgroups can be made in two ways. Seeking most rapid genetic gain may involve using many young dams despite their poorer maternal ability. Making proper allowances for genetic age effects is similar in principle to making allowance for genetic trend and for parental breeding value in BLUP methods. Matrix methods of predicting response to selection are illustrated by an example with disproportionate selection from parental-age subgroups. Proper specification of an appropriate control population is essential for evaluation of genetic gains, but if a control population is established from a line previously under selection it may show appreciable fluctuations in mean quite separate from genetic drift, and the final control population mean may be significantly different from the initial mean even in the absence of environmental change. The relative contributions of the control line and the selection line to fluctuations in genetic gain depend on the initial conditions.